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Add nrow and ncol fallback implementations (#343)
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@bkamins
bkamins authored Sep 19, 2023
1 parent 1b5bbe2 commit a695836
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2 changes: 1 addition & 1 deletion Project.toml
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@@ -1,7 +1,7 @@
name = "Tables"
uuid = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
authors = ["quinnj <[email protected]>"]
version = "1.10.1"
version = "1.11.0"

[deps]
DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
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28 changes: 15 additions & 13 deletions docs/src/index.md
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Expand Up @@ -229,19 +229,21 @@ make my custom type valid for Tables.jl consumers?
For a type `MyTable`, the interface to becoming a proper table is straightforward:
| Required Methods | Default Definition | Brief Description |
|----------------------------------------|------------------------------|---------------------------------------------------------------------------------------------------------------------------------|
| `Tables.istable(::Type{MyTable})` | | Declare that your table type implements the interface |
| **One of:** | | |
| `Tables.rowaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.rows(::MyTable)` method |
| `Tables.rows(x::MyTable)` | | Return an `Tables.AbstractRow`-compatible iterator from your table |
| **Or:** | | |
| `Tables.columnaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.columns(::MyTable)` method |
| `Tables.columns(x::MyTable)` | | Return an `Tables.AbstractColumns`-compatible object from your table |
| **Optional methods** | | |
| `Tables.schema(x::MyTable)` | `Tables.schema(x) = nothing` | Return a [`Tables.Schema`](@ref) object from your `Tables.AbstractRow` iterator or `Tables.AbstractColumns` object; or `nothing` for unknown schema |
| `Tables.materializer(::Type{MyTable})` | `Tables.columntable` | Declare a "materializer" sink function for your table type that can construct an instance of your type from any Tables.jl input |
| `Tables.subset(x::MyTable, inds; viewhint)` | | Return a row or a sub-table of the original table
| Required Methods | Default Definition | Brief Description |
|----------------------------------------------|------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|
| `Tables.istable(::Type{MyTable})` | | Declare that your table type implements the interface |
| **One of:** | | |
| `Tables.rowaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.rows(::MyTable)` method |
| `Tables.rows(x::MyTable)` | | Return an `Tables.AbstractRow`-compatible iterator from your table |
| **Or:** | | |
| `Tables.columnaccess(::Type{MyTable})` | | Declare that your table type defines a `Tables.columns(::MyTable)` method |
| `Tables.columns(x::MyTable)` | | Return an `Tables.AbstractColumns`-compatible object from your table |
| **Optional methods** | | |
| `Tables.schema(x::MyTable)` | `Tables.schema(x) = nothing` | Return a [`Tables.Schema`](@ref) object from your `Tables.AbstractRow` iterator or `Tables.AbstractColumns` object; or `nothing` for unknown schema |
| `Tables.materializer(::Type{MyTable})` | `Tables.columntable` | Declare a "materializer" sink function for your table type that can construct an instance of your type from any Tables.jl input |
| `Tables.subset(x::MyTable, inds; viewhint)` | | Return a row or a sub-table of the original table |
| `DataAPI.nrow(x::MyTable)` | | Return number of rows of table `x` |
| `DataAPI.ncol(x::MyTable)` | | Return number of columns of table `x` |
Based on whether your table type has defined `Tables.rows` or `Tables.columns`, you then ensure that the `Tables.AbstractRow` iterator
or `Tables.AbstractColumns` object satisfies the respective interface.
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5 changes: 5 additions & 0 deletions src/dicts.jl
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Expand Up @@ -197,3 +197,8 @@ function dictrowtable(x)
end
return DictRowTable(names, types, out)
end

# implement default nrow and ncol methods for DataAPI.jl

DataAPI.nrow(table::DictRowTable) = length(table)
DataAPI.ncol(table::DictRowTable) = length(getfield(table, :names))
9 changes: 9 additions & 0 deletions src/fallbacks.jl
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Expand Up @@ -275,3 +275,12 @@ columnnames(x::CopiedColumns) = columnnames(source(x))
end
throw(ArgumentError("no default `Tables.columns` implementation for type: $T"))
end

# implement default nrow and ncol methods for DataAPI.jl

# this covers also MatrixTable
DataAPI.nrow(table::AbstractColumns) = rowcount(table)
DataAPI.ncol(table::AbstractColumns) = length(columnnames(table))

DataAPI.nrow(table::AbstractRowTable) = length(table)
DataAPI.ncol(table::AbstractRowTable) = isempty(table) ? 0 : length(columnnames(first(table)))
5 changes: 5 additions & 0 deletions src/matrix.jl
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Expand Up @@ -111,3 +111,8 @@ function matrix(table::MatrixTable; transpose::Bool=false)
return matrix
end
end

# implement default nrow and ncol methods for DataAPI.jl

DataAPI.nrow(table::MatrixRowTable) = length(table)
DataAPI.ncol(table::MatrixRowTable) = size(getfield(table, :matrix), 2) # this is correct even if m is a vector
8 changes: 8 additions & 0 deletions src/namedtuples.jl
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Expand Up @@ -190,3 +190,11 @@ function columntable(itr::T) where {T}
return columntable(schema(cols), cols)
end
columntable(x::ColumnTable) = x

# implement default nrow and ncol methods for DataAPI.jl

DataAPI.nrow(table::ColumnTable) = isempty(table) ? 0 : length(first(table))
DataAPI.ncol(table::ColumnTable) = length(table)

DataAPI.nrow(table::RowTable) = length(table)
DataAPI.ncol(table::RowTable) = isempty(table) ? 0 : length(first(table))
57 changes: 54 additions & 3 deletions test/runtests.jl
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using Test, Tables, OrderedCollections, TableTraits, DataValues, QueryOperators, IteratorInterfaceExtensions, SparseArrays
using Test, Tables, OrderedCollections, TableTraits, DataValues, QueryOperators, IteratorInterfaceExtensions, SparseArrays, DataAPI

@testset "utils.jl" begin

Expand Down Expand Up @@ -957,7 +957,7 @@ end
@test Tables.istable(Vector{Dict{String}})
@test Tables.istable(Vector{Dict{SubString}})
@test Tables.istable(Vector{Dict{AbstractString}})

@test Set(Tables.columnnames(Dict(:a=>1, :b=>2))) == Set([:a, :b])
@test Set(Tables.columnnames(Dict("a"=>1, "b"=>2))) == Set([:a, :b])
@test Set(Tables.columnnames(Dict("a"=>1, SubString("b")=>2))) == Set([:a, :b])
Expand All @@ -976,4 +976,55 @@ end
@test Tables.getcolumn(Dict("a"=>1, SubString("b")=>2), Int, 1, :a) == 1
@test Tables.getcolumn(Dict(SubString("a")=>1, SubString("b")=>2), Int, 1, :a) == 1
end


@testset "test nrow and ncol" begin
# AbstractColumns
@test DataAPI.nrow(Tables.CopiedColumns(NamedTuple())) == 0
@test DataAPI.ncol(Tables.CopiedColumns(NamedTuple())) == 0
@test DataAPI.nrow(Tables.CopiedColumns((a=1:3, b=2:4))) == 3
@test DataAPI.ncol(Tables.CopiedColumns((a=1:3, b=2:4))) == 2

# ColumnTable
@test DataAPI.nrow(NamedTuple()) == 0
@test DataAPI.ncol(NamedTuple()) == 0
@test DataAPI.nrow((a=1:3, b=2:4)) == 3
@test DataAPI.ncol((a=1:3, b=2:4)) == 2

# AbstractRowTable
@test DataAPI.nrow(collect(Tables.rows(Tables.table(ones(0, 0))))) == 0
@test DataAPI.ncol(collect(Tables.rows(Tables.table(ones(0, 0))))) == 0
@test DataAPI.nrow(collect(Tables.rows(Tables.table(ones(2, 3))))) == 2
@test DataAPI.ncol(collect(Tables.rows(Tables.table(ones(2, 3))))) == 3

# RowTable
@test DataAPI.nrow(NamedTuple[]) == 0
@test DataAPI.ncol(NamedTuple[]) == 0
@test DataAPI.nrow([(a=1,b=2), (a=3, b=4), (a=5, b=6)]) == 3
@test DataAPI.ncol([(a=1, b=2), (a=3, b=4), (a=5, b=6)]) == 2

# MatrixTable
@test DataAPI.nrow(Tables.table(ones(0, 0))) == 0
@test DataAPI.ncol(Tables.table(ones(0, 0))) == 0
@test DataAPI.nrow(Tables.table(ones(2, 3))) == 2
@test DataAPI.ncol(Tables.table(ones(2, 3))) == 3
@test DataAPI.nrow(Tables.table([])) == 0
@test DataAPI.ncol(Tables.table([])) == 1
@test DataAPI.nrow(Tables.table([1, 2])) == 2
@test DataAPI.ncol(Tables.table([1, 2])) == 1

# MatrixRowTable
@test DataAPI.nrow(Tables.rows(Tables.table(ones(0, 0)))) == 0
@test DataAPI.ncol(Tables.rows(Tables.table(ones(0, 0)))) == 0
@test DataAPI.nrow(Tables.rows(Tables.table(ones(2, 3)))) == 2
@test DataAPI.ncol(Tables.rows(Tables.table(ones(2, 3)))) == 3
@test DataAPI.nrow(Tables.rows(Tables.table([]))) == 0
@test DataAPI.ncol(Tables.rows(Tables.table([]))) == 1
@test DataAPI.nrow(Tables.rows(Tables.table([1, 2]))) == 2
@test DataAPI.ncol(Tables.rows(Tables.table([1, 2]))) == 1

# DictRowTable
@test DataAPI.nrow(Tables.dictrowtable(NamedTuple[])) == 0
@test DataAPI.ncol(Tables.dictrowtable(NamedTuple[])) == 0
@test DataAPI.nrow(Tables.dictrowtable([(a=1, b=2), (a=3, b=4), (a=5, b=6)])) == 3
@test DataAPI.ncol(Tables.dictrowtable([(a=1, b=2), (a=3, b=4), (a=5, b=6)])) == 2
end

3 comments on commit a695836

@bkamins
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Registration pull request created: JuliaRegistries/General/91716

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v1.11.0 -m "<description of version>" a69583674e697a3fc329d2ec405d8ffdf29d6c00
git push origin v1.11.0

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CC @quinnj @nalimilan
@ronisbr - now you have a proper support for nrow and ncol for PrettyTables.jl.

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